WO2022012017A1 - 一种基于机器视觉的卷烟飞灰检测装置及检测方法 - Google Patents

一种基于机器视觉的卷烟飞灰检测装置及检测方法 Download PDF

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WO2022012017A1
WO2022012017A1 PCT/CN2021/073110 CN2021073110W WO2022012017A1 WO 2022012017 A1 WO2022012017 A1 WO 2022012017A1 CN 2021073110 W CN2021073110 W CN 2021073110W WO 2022012017 A1 WO2022012017 A1 WO 2022012017A1
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cigarette
ash
fly ash
column
image
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PCT/CN2021/073110
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English (en)
French (fr)
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詹建波
郑晗
王浩
王旭
谢姣
余婷婷
程量
李利伟
岳保山
丁海燕
余耀
李向珍
余江
张静
孔令汉
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云南中烟工业有限责任公司
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Publication of WO2022012017A1 publication Critical patent/WO2022012017A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8806—Specially adapted optical and illumination features
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N31/00—Investigating or analysing non-biological materials by the use of the chemical methods specified in the subgroup; Apparatus specially adapted for such methods
    • G01N31/12—Investigating or analysing non-biological materials by the use of the chemical methods specified in the subgroup; Apparatus specially adapted for such methods using combustion
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G01N2021/8874—Taking dimensions of defect into account
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

Definitions

  • the invention belongs to the technical field of cigarette fly ash detection, relates to a method for detecting cigarette fly ash, and in particular relates to a cigarette fly ash detection device and detection method based on machine vision.
  • the method of treatment judges, compares and calculates the situation of cigarette fly ash.
  • the research methods for the ash-packaging performance of cigarettes are mainly through the comparison and evaluation of the pros and cons of the tuff effect of the formed ash column after the cigarette is left to burn.
  • the current method uses static combustion or static evaluation of cigarette ash performance under smoking conditions, while consumers are concerned about the quality of cigarette ash during smoking. It can be seen that the current method can only compare and evaluate the overall ash column of the cigarette after combustion, and then guide the improvement of the performance and quality of the cigarette pack, and cannot objectively reflect the ash falling and fly ash of the cigarette during the smoking process.
  • the present invention proposes a cigarette fly ash index.
  • the fly ash characterizes the soot that escapes from the cigarette ash column during the smoking process and in the process of non-bombing soot. Fly ash may cause pollution, burn consumers’ clothes, cause disgust among surrounding non-smokers, and cause fire hazards. It can be seen that, based on consumer demand and safety, it is of great significance to study the reduction of fly ash during cigarette smoking.
  • the purpose of the present invention is to solve the deficiencies of the prior art, and propose a cigarette fly ash detection device and detection method based on machine vision.
  • the quantitative detection method of fly ash that is, the characterization of cigarette ash from the ash column, falling and falling, using machine vision to track the burning state of cigarettes in real time, and using image processing to track and judge the situation of cigarette fly ash, through objective and accurate characterization Cigarette fly ash index is used to guide cigarette formulation research and quality optimization and upgrading.
  • a cigarette fly ash detection device based on machine vision comprising a manipulator for simulating human smoking action, a cigarette holder, a cigarette suction tube, a bomb ash mechanism, an image acquisition device and an image processing device;
  • a cigarette holder is fixedly connected to the working end of the manipulator simulating the human suction action
  • the cigarette holder is connected with the cigarette suction pipe;
  • the ash-bombing mechanism is arranged on the periphery of the manipulator simulating the suction action of the human body;
  • the image processing device is connected with the image acquisition device
  • the image acquisition device is also installed on the working end of the manipulator simulating the suction action of the human body
  • the manipulator for simulating human smoking action is used for simulating human smoking action
  • the cigarette holder is used for holding cigarettes with different specifications such as different circumferences
  • the cigarette suction pipe is connected to the suction cylinder for smoking cigarettes;
  • the ash-bombing mechanism is used for simulating the cigarette soot during the smoking process
  • the image acquisition device is used for synchronously acquiring the image of the cigarette burning ash column during the smoking process
  • the image processing device is used to compare and analyze the images of the cigarette burning ash column synchronously collected by the image acquisition device during the simulated smoking process, and compare the images under the condition of no bomb ash.
  • the change of the crack area of the column is used to judge whether there is a new defect in the cigarette combustion ash column.
  • the image acquisition device includes N cameras, and N ⁇ 2.
  • the ash bomb mechanism includes a cigarette holder located on the periphery of the mechanical arm, a drive motor mounted on the cigarette holder, and a pull rod provided at the output end of the drive motor.
  • the image processing device performs statistics on the amount of fly ash present in the entire cigarette within the range of the set burning length of the detection sample.
  • the present invention also provides a machine vision-based cigarette fly ash detection method, which adopts the above-mentioned machine vision-based cigarette fly ash detection device to measure, comprising the following steps:
  • step (1) the cigarette is clamped on the cigarette holder and adjusted so that the whole cigarette is in the picture captured by the camera of the image capture device;
  • Step (2) ignite the cigarette on the cigarette holder, and collect the image of the cigarette in the simulated smoking process in real time by the image acquisition device;
  • Step (3) after the image processing device performs condition screening on the collected images, and compares the changes in the crack area of the cigarette burning ash column in the images collected before and after in the non-bombing process, to determine whether the cigarette burning ash column appears.
  • New defects such as new defects, it is judged that fly ash is present, and the amount of fly ash is represented by the area of the new crack;
  • the specific implementation method is to collect the ash column images when the cigarette is burning in real time and calculate the crack area of the ash column, and screen out the moment when the crack area changes greatly in the adjacent collected images, and consider that fly ash occurs at this time.
  • the combustion length range of the selected test sample the number of areas where fly ash appears in the cigarette and the area of each area are counted to judge the quality of the fly ash characteristics of the brand of cigarette.
  • an image is acquired every 1 s.
  • the specific method for judging whether the cigarette burning ash column has a new defect is: every 1s, compare the two pictures used before and after whether there is an obvious grayscale change, if there is an obvious change in the crack area. , indicating that a new defect has occurred.
  • the obvious change of the crack area is in the range of 1-20mm 2, aiming to ignore the newly generated crack area due to natural combustion
  • the steps of calculating the crack area of the ash column are as follows:
  • the approximate area of the ash column is obtained according to the position of the carbon wire and the end position of the ash column;
  • the first binarization is performed on the image of the general area of the gray column, and then the contour is searched to filter the environmental influence to obtain an accurate gray column area;
  • the second binarization is performed on the accurate ash column area to obtain the crack area of the ash column, so as to calculate the crack area of the ash column in the current picture.
  • the smoking action of the human body includes characteristic actions and trajectories such as simulating smoking, sitting at a desk, flicking soot, and turning wrist after smoking;
  • the adjustment in step (1) includes adjusting the position and angle of the camera, adjusting the length of the cigarette clamping, and the like.
  • the present invention has the following beneficial effects:
  • the cigarette fly ash index is put forward, which can objectively and accurately reflect the ash column falling off of cigarettes that consumers are concerned about in the process of smoking cigarettes under the condition of non-bomb ash;
  • this method overcomes the influence of subjective factors and provides a quantitative detection method with good repeatability, objectivity and high reliability. It can more accurately evaluate product differences, guide the research on related cigarette formulations, and improve the quality of cigarettes.
  • Fig. 1 is the structural representation of the cigarette fly ash detection device based on machine vision of the present invention
  • Fig. 2 is a schematic diagram of the relative position structure of the manipulator and the ash-bombing mechanism for simulating the suction action of the human body;
  • Figure 3 is an image collected during detection
  • Figure 4 is another image collected during detection
  • Fig. 5 is the partial schematic diagram of the picture before the fly ash appears
  • Fig. 6 is the partial schematic diagram of the picture after the occurrence of fly ash
  • Figure 7 is a comparison image of fly ash at different shooting angles for samples of various specifications
  • Fig. 8 is the schematic diagram of calculating ash column crack area processing process
  • Fig. 9 is the original image collected when a certain brand of cigarette is detected.
  • FIG. 10 is an image of the approximate area of the ash column obtained according to FIG. 9;
  • Fig. 11 is the image obtained after the first binarization according to Fig. 10;
  • Figure 12 is an accurate ash column area image obtained according to Figure 11;
  • FIG. 13 is an image obtained after the first binarization according to FIG. 12 .
  • plural means two or more.
  • the orientation or state relationship indicated by the terms “inside”, “upper”, “lower”, etc. is based on the orientation or state relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying the indicated A device or element must have a particular orientation, be constructed and operate in a particular orientation, and therefore should not be construed as limiting the invention.
  • the terms “installed”, “connected” and “provided with” should be understood in a broad sense, for example, it may be a fixed connection or a Removal connection, or integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium.
  • installed e.g., it may be a fixed connection or a Removal connection, or integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium.
  • a machine vision-based cigarette fly ash detection device includes a manipulator 1 that simulates human smoking action, a cigarette holder 2, a cigarette suction tube 3, a bomb ash mechanism 4, and an image acquisition mechanism. device 5 and image processing device 6;
  • a cigarette holder 2 is fixedly connected to the working end of the manipulator 1 simulating the human suction action;
  • the cigarette holder 2 is connected with the cigarette suction pipe 3;
  • the ash bomb mechanism 4 is arranged on the periphery of the manipulator 1 simulating the suction action of the human body;
  • the image processing device 6 is connected with the image acquisition device 5;
  • the image acquisition device 5 is also installed on the working end of the manipulator 1 simulating the suction action of the human body;
  • the described manipulator 1 for simulating human smoking action is used for simulating the smoking action of human body
  • the cigarette holder 2 is used for holding cigarettes with different specifications such as different circumferences;
  • the cigarette suction pipe 3 is connected to the suction cylinder for smoking cigarettes;
  • the described bomb ash mechanism 4 is used for simulating the cigarette soot during the smoking process
  • the image acquisition device 5 is used for synchronously acquiring the image of the cigarette burning ash column during the smoking process
  • the image processing device 6 is used to compare and analyze the images of the cigarette burning ash column synchronously collected by the image acquisition device 5 during the simulated smoking process, and compare the images under the condition of no bomb ash.
  • the change of the crack area of the combustion ash column is used to judge whether there is a new defect in the combustion ash column of the cigarette.
  • the image acquisition device 5 includes N cameras, and N ⁇ 2.
  • the ash bomb mechanism 4 includes a cigarette holder 7 located on the periphery of the mechanical arm, a drive motor 8 mounted on the cigarette holder 7 , and a pull rod 9 arranged at the output end of the drive motor 8 .
  • the ISO, FTC, Massachusetts or Canadian deep smoking mode is used when simulating the smoking action of a human cigarette.
  • the image processing device 6 counts the amount of fly ash that occurs in the entire cigarette within the range of the set burning length of the detection sample.
  • a cigarette fly ash detection method based on machine vision using the above-mentioned machine vision-based cigarette fly ash detection device to measure, comprising the following steps:
  • Step 1 clamping the cigarette on the cigarette holder and adjusting it so that the whole cigarette is in the picture captured by the camera of the image capturing device;
  • Step 2 igniting the cigarette on the cigarette holder, and collecting the image of the cigarette in the simulated smoking process in real time through the image acquisition device;
  • Step 3 After the image processing device performs condition screening on the collected images, it compares the changes in the crack area of the cigarette burning ash column in the images collected before and after in the non-bombing process to determine whether a new cigarette burning ash column appears. Defects, if there is a new defect, it is judged that fly ash is present, and the amount of fly ash is represented by the area of the new crack;
  • the combustion length range of the selected test sample the number of areas where fly ash appears in the cigarette and the area of each area are counted to judge the quality of the fly ash characteristics of the brand of cigarette.
  • an image is acquired every 1 s.
  • the specific method for judging whether there is a new defect in the cigarette burning ash column is: every 1 s, check whether there is an obvious grayscale change between the two pictures used before and after the comparison, and if there is an obvious change in the crack area, it indicates that new defect.
  • the apparent change in the breach area is in the range of 1-20 mm 2 .
  • the steps for calculating the crack area of the ash column are as follows:
  • the approximate area of the ash column is obtained according to the position of the carbon wire and the end position of the ash column;
  • the second step is to perform the first binarization on the image of the general area of the gray column, and then search for the contour to obtain an accurate gray column area;
  • the second binarization is performed on the accurate ash column area to obtain the crack area of the ash column, so as to calculate the crack area of the ash column in the current picture.
  • the actual processing diagram is shown in Figure 9-13.
  • the dotted line represents the burning carbon line
  • the box represents the detection area.
  • the detection area changes with the combustion line, which can significantly reduce external interference.
  • the cigarette paper of the cigarette is mostly white or light-colored, while the burning carbon line of the cigarette is black or dark. According to this feature, the present invention can track the burning position of the cigarette in real time. According to the position of the burning carbon line, track the burning position of the cigarette.
  • the LED light source is used to illuminate and fill the sample detection environment during the image acquisition process, the purpose is to ensure that the detection environment light is sufficient and stable, and to reduce the interference of the external environment on the image acquisition.
  • Test sample This test method is applicable to all samples of cigarette specifications.
  • a conventional cigarette with a circumference of 24.3 mm and a length of 84.0 mm is used as the description of the test sample.
  • the test is carried out according to the above-mentioned embodiment, and a total of 3 different cigarette specifications are tested.
  • Test configuration Control system: Analysis software: FZ-PanDA (OMRON Japan); Lighting source: JL-LR-100X30 (Made in Jiali); Camera model: FH-SC04 (OMRON Japan), lens model: 3Z4S-LE ( Japan OMRON).
  • Test environment temperature: (22 ⁇ 2)°C, relative humidity: (60 ⁇ 5)%.
  • Step (1) place the single layer of the cigarette sample to be tested evenly in the environment specified in GB/T 16447 to balance for 48h;
  • Step (2) clamping the balanced sample cigarette on the cigarette holder, and adjusting the position of the image acquisition device, so that the entire cigarette is located at the image acquisition center position of each camera;
  • Step (3) open the image acquisition device and the image processing device
  • step (4) the cigarette of the test sample is ignited, the simulated suction of the manipulator and the cigarette suction cylinder are activated, and the detection is carried out under the ISO standard suction condition.
  • the simulated suction action of the manipulator is set according to the waiting time of 40s at the desk, the smoking angle at the desk is 30°, and the wrist is turned 90° after suction; when the change of the crack area exceeds 1mm 2 , it is judged that a new defect has occurred;
  • step (5) the image acquisition device collects an image every 1 s according to the setting, and collects an image of the cigarette burning process in real time;
  • Step (6) after the image processing device performs condition screening on the collected images, compares the changes in the crack area of the cigarette burning ash column in the images collected before and after in the non-bombing process to determine whether the cigarette burning ash column appears.
  • New defects such as new defects, determine the presence of fly ash, calculate the amount of fly ash according to the difference, and use the area to characterize.
  • step (7) time and image records are performed on the samples in which fly ash occurs during the detection, and two samples are selected for each specification sample to characterize the fly ash results, as shown in Table 1 and FIG. 7 .
  • the method of the invention can effectively collect and quantify the cigarette fly ash, which is used to compare the quality difference of the cigarette product fly ash and guide the optimization and upgrading of the cigarette product.

Abstract

一种基于机器视觉的卷烟飞灰检测装置及检测方法，属于卷烟飞灰检测技术领域。通过仿真人体卷烟抽吸动作机械手（1）夹持检测样品，在仿真人体抽吸过程中，采用多组摄像头对卷烟燃烧过程进行同步全信息实时跟拍，在非弹击烟灰条件下，通过采集图像差异对比，对卷烟燃烧灰柱烟灰飞离、脱落的裂口面积变化进行识别，从而计算表征在定点弹烟灰处以外散落的卷烟飞灰情况。克服了主观因素影响，提供了重复性好、客观、可信度高的量化检测方法，能更加精准地评价产品差异，指导相关卷烟配方研究工作，提升卷烟品质。

Description

一种基于机器视觉的卷烟飞灰检测装置及检测方法 技术领域
本发明属于卷烟飞灰检测技术领域，涉及一种检测卷烟飞灰的方法，具体涉及一种基于机器视觉的卷烟飞灰检测装置及检测方法，该方法采用机器视觉实时跟踪卷烟燃烧状态，采用图像处理的方式判断、对比、计算卷烟飞灰的情况。
背景技术
随着卷烟技术的发展及消费者对卷烟抽吸品质要求的不断提高，卷烟在抽吸过程中燃烧包灰性能的优劣越来越受到消费者的关注，同时，由于抽吸过程中烟灰掉落情况还存在引发火灾的潜在危险，所以如何提升卷烟燃烧包灰性能一直都是烟草行业研究的重要方向之一。
目前，对卷烟燃烧包灰性能的研究方法主要通过卷烟在静置燃烧后，对形成的灰柱的凝灰效果优劣状况进行对比和评价。需要注意的是，目前方法通过静燃或在抽吸条件下静态评价卷烟包灰性能，而消费者关注的是卷烟在抽吸过程中的卷烟包灰质量优劣。可见，采用现行方法仅能对燃烧后卷烟整体灰柱进行对比评价，进而指导卷烟包灰性能质量改进提升，并不能客观地反应出卷烟抽吸过程中卷烟的落灰、飞灰情况。
针对上述情况和技术不足，本发明提出了卷烟飞灰指标，飞灰表征的是卷烟在抽吸过程中，在非弹烟灰的过程，脱离卷烟灰柱的烟灰。飞灰可能造成污染、烧损消费者衣服，引发周边非吸烟者反感，存在火灾隐患等情况，可见，以消费需求和安全为导向，研究降低卷烟抽吸过程中的飞灰具有重要意义。
基于现有检测技术不足，同时，由于卷烟燃烧过程中飞灰指标特性，具有测量精度要求高、测量样本数量多、飞灰状态持续时间短等特点，很难通过人工的方式进行检测。所以，开发适用于卷烟研制和卷烟飞灰特性的检测设备十分必要。
发明内容
本发明的目的是为了解决现有技术的不足，提出了一种基于机器视觉的卷烟飞灰检测装置及检测方法，该方法是针对卷烟抽吸过程中，在非弹烟灰的状态下，对卷烟飞灰的量化检测方法，即卷烟烟灰脱离烟灰柱，飘落散落的情况表征，采用机器视觉实时跟踪卷烟燃烧状态，并采用图像处理的方式跟踪和判断卷烟飞灰的情况，通过客观、精确地表征卷烟飞灰指标，用于指导卷烟配方 研究和质量优化升级。
为实现上述目的，本发明采用的技术方案如下：
一种基于机器视觉的卷烟飞灰检测装置，包括仿真人体抽吸动作机械手、卷烟夹持器、烟支抽吸管、弹灰机构、图像采集装置和图像处理装置；
仿真人体抽吸动作机械手工作端处固定连接有卷烟夹持器；
卷烟夹持器与烟支抽吸管相连；
弹灰机构设于仿真人体抽吸动作机械手外围；
图像处理装置与图像采集装置相连；
图像采集装置也安装在仿真人体抽吸动作机械手工作端；
所述的仿真人体抽吸动作机械手用于模拟人体抽烟动作；
所述的卷烟夹持器用于夹持不同圆周等规格差异的卷烟；
所述的烟支抽吸管连接抽吸气缸，用于抽吸卷烟；
所述的弹灰机构用于仿真抽吸过程中点弹卷烟烟灰；
所述的图像采集装置用于同步采集卷烟在抽吸过程中卷烟燃烧灰柱图像；
所述的图像处理装置用于对所述的图像采集装置在仿真抽吸过程中同步采集到的卷烟燃烧灰柱图像进行对比分析，对比不进行弹灰条件下的图像，通过图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
其中，对比的两张图像之间不存在弹灰动作。
进一步，优选的是，图像采集装置包括N个摄像头，N≥2。
进一步，优选的是，弹灰机构包括位于机械臂外围的弹烟支架，安装于弹烟支架上的驱动电机，设置于驱动电机输出端的拔杆。
进一步，优选的是，仿真人体卷烟抽吸动作时，采用ISO、FTC、Massac husetts或加拿大深度抽吸模式。
进一步，优选的是，图像处理装置在判断出现飞灰后，在设定检测样品燃烧长度范围内，对整支烟的出现飞灰量进行统计。
本发明同时提供一种基于机器视觉的卷烟飞灰检测方法，采用上述基于机器视觉的卷烟飞灰检测装置进行测定，包括如下步骤：
步骤(1)，将卷烟夹持在卷烟夹持器上，并进行调整，使得整只卷烟在图像采集装置的摄像头采集的画面中；
步骤(2)，点燃卷烟夹持器上的卷烟，通过图像采集装置实时采集卷烟在 仿真抽吸过程中的图像；
步骤(3)，图像处理装置对采集到的图像进行条件筛选后，对比在非弹灰过程中，前后采集到的图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
具体实现方法为实时采集烟支燃烧时的灰柱图像并计算灰柱的裂口面积，筛选得到相邻采集图像中裂口面积变化较大的时刻，并认为此时发生飞灰。
之后根据选择检测样品的燃烧长度范围，对该烟支出现飞灰的区域的数量及各区域的面积进行统计，用于判断该品牌烟支的飞灰特性的优劣。
进一步，优选的是，图像采集装置实时采集卷烟燃烧过程的图像时，每隔1s采集一张图像。
进一步，优选的是，判断卷烟燃烧灰柱是否出现了新的缺损的具体方法是：每隔1s，对比前后采用的两张图片是否出现了明显的灰度变化，若出现了明显的裂口面积变化，则表明出现了新的缺损。
进一步，优选的是，明显的裂口面积变化取值范围1-20mm 2，旨在忽略由于自然燃烧新产生的裂口面积
进一步，优选的是，计算灰柱裂口面积步骤如下：
第一步，根据炭线位置和灰柱末端位置获得灰柱的大致区域；
第二步，对灰柱大致区域图片进行第一次二值化，再查找轮廓，从而过滤环境影响以获得准确的灰柱区域；
第三步，对准确的灰柱区域进行第二次二值化，获得灰柱的裂口区域，从而计算出当前图片灰柱的裂口面积。
所述的人体抽烟动作包括模拟抽吸、伏案、弹烟灰、抽吸后手腕翻转等特征动作和轨迹；
步骤(1)中调整包括调整摄像头所在位置、角度，调整卷烟夹持的长度等。
本发明与现有技术相比，其有益效果为：
1.提出了卷烟飞灰指标，能客观、准确反映消费者在抽吸卷烟过程中关注的卷烟在非弹烟灰条件下灰柱脱落的情况；
2.建立了一套基于仿真人体卷烟抽吸过程动作，采用图像差异法采集、处理量化卷烟燃烧飞灰的检测方法，检测方法快捷、精准、易于推广；
3.采用多角度全视觉同步跟拍卷烟燃烧状态，提高了卷烟飞灰采集的精确 度；
4.相对采用人工抽吸经验和主观判断卷烟是否发生飞灰以及飞灰量的大小的方法，本方法克服了主观因素影响，提供了重复性好、客观、可信度高的量化检测方法，能更加精准地评价产品差异，指导相关卷烟配方研究工作，提升卷烟品质。
附图说明
图1为本发明基于机器视觉的卷烟飞灰检测装置的结构示意图；
图2为仿真人体抽吸动作机械手及弹灰机构的相对位置结构示意图；
其中，1、仿真人体抽吸动作机械手；2、卷烟夹持器；3、烟支抽吸管；4、弹灰机构；5、图像采集装置；6、图像处理装置；7、弹烟支架；8、驱动电机；9、拔杆；10、卷烟；
图3为检测时，采集到的一张图像；
图4为检测时，采集到的另一张图像；
图5为出现飞灰前的图片的局部示意图；
图6为出现飞灰后的图片的局部示意图；
图7为各规格样品不同拍摄角度飞灰对比图像；
图8为计算灰柱裂口面积处理过程的示意图；
图9为某牌号卷烟检测时采集的原图像；
图10为根据图9获得灰柱的大致区域的图像；
图11为根据图10第一次二值化后得到的图像；
图12为根据图11获得灰柱的准确的灰柱区域图像；
图13为根据图12第一次二值化后得到的图像。
具体实施方式
下面结合实施例对本发明作进一步的详细描述。
本领域技术人员将会理解，下列实施例仅用于说明本发明，而不应视为限定本发明的范围。实施例中未注明具体技术或条件者，按照本领域内的文献所描述的技术或条件或者按照产品说明书进行。所用材料或设备未注明生产厂商者，均为可以通过购买获得的常规产品。
本技术领域技术人员可以理解，除非特意声明，这里使用的单数形式“一”、“一个”、“所述”和“该”也可包括复数形式。应该进一步理解的是，本发明的说明书中使用的措辞“包括”是指存在所述特征、整数、步骤、操作、元件和 /或组件，但是并不排除存在或添加一个或多个其他特征、整数、步骤、操作、元件、组件和/或它们的组。应该理解，当我们称元件被“连接”到另一元件时，它可以直接连接到其他元件，或者也可以存在中间元件。此外，这里使用的“连接”可以包括无线连接。
在本发明的描述中，除非另有说明，“多个”的含义是两个或两个以上。术语“内”、“上”、“下”等指示的方位或状态关系为基于附图所示的方位或状态关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。
在本发明的描述中，需要说明的是，除非另有明确的规定和限定，术语“安装”、“连接”、“设有”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是机械连接，也可以是电连接；可以是直接相连，也可以通过中间媒介间接相连。对于本领域的普通技术人员而言，根据具体情况理解上述术语在本发明中的具体含义。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)具有与本发明所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非像这里一样定义，不会用理想化或过于正式的含义来解释。
如图1和图2所示，一种基于机器视觉的卷烟飞灰检测装置，包括仿真人体抽吸动作机械手1、卷烟夹持器2、烟支抽吸管3、弹灰机构4、图像采集装置5和图像处理装置6；
仿真人体抽吸动作机械手1工作端处固定连接有卷烟夹持器2；
卷烟夹持器2与烟支抽吸管3相连；
弹灰机构4设于仿真人体抽吸动作机械手1外围；
图像处理装置6与图像采集装置5相连；
图像采集装置5也安装在仿真人体抽吸动作机械手1工作端；
所述的仿真人体抽吸动作机械手1用于模拟人体抽烟动作；
所述的卷烟夹持器2用于夹持不同圆周等规格差异的卷烟；
所述的烟支抽吸管3连接抽吸气缸，用于抽吸卷烟；
所述的弹灰机构4用于仿真抽吸过程中点弹卷烟烟灰；
所述的图像采集装置5用于同步采集卷烟在抽吸过程中卷烟燃烧灰柱图像；
所述的图像处理装置6用于对所述的图像采集装置5在仿真抽吸过程中同步采集到的卷烟燃烧灰柱图像进行对比分析，对比不进行弹灰条件下的图像，通过图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
其中，对比的两张图像之间不存在弹灰动作。
优选，图像采集装置5包括N个摄像头，N≥2。
优选，弹灰机构4包括位于机械臂外围的弹烟支架7，安装于弹烟支架7上的驱动电机8，设置于驱动电机8输出端的拔杆9。
优选，仿真人体卷烟抽吸动作时，采用ISO、FTC、Massachusetts或加拿大深度抽吸模式。
优选，图像处理装置6在判断出现飞灰后，在设定检测样品燃烧长度范围内，对整支烟的出现飞灰量进行统计。
一种基于机器视觉的卷烟飞灰检测方法，采用上述的基于机器视觉的卷烟飞灰检测装置进行测定，包括如下步骤：
步骤1，将卷烟夹持在卷烟夹持器上，并进行调整，使得整只卷烟在图像采集装置的摄像头采集的画面中；
步骤2，点燃卷烟夹持器上的卷烟，通过图像采集装置实时采集卷烟在仿真抽吸过程中的图像；
步骤3，图像处理装置对采集到的图像进行条件筛选后，对比在非弹灰过程中，前后采集到的图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
之后根据选择检测样品的燃烧长度范围，对该烟支出现飞灰的区域的数量及各区域的面积进行统计，用于判断该品牌烟支的飞灰特性的优劣。
优选，图像采集装置实时采集卷烟燃烧过程的图像时，每隔1s采集一张图像。
优选，判断卷烟燃烧灰柱是否出现了新的缺损的具体方法是：每隔1s，对比前后采用的两张图片是否出现了明显的灰度变化，若出现了明显的裂口面积变化，则表明出现了新的缺损。
优选，明显的裂口面积变化取值范围1-20mm 2。
优选，如图8所示，计算灰柱裂口面积步骤如下：
第一步，根据炭线位置和灰柱末端位置获得灰柱的大致区域；
第二步，对灰柱大致区域图片进行第一次二值化，再查找轮廓，获得准确的灰柱区域；
第三步，对准确的灰柱区域进行第二次二值化，获得灰柱的裂口区域，从而计算出当前图片灰柱的裂口面积。实际处理图如图9-13。
图3和图4中，虚线表示燃烧碳线，方框表示检测区域，检测区域随着燃烧线变化，可以显著减少外界干扰。卷烟的卷烟纸多为白色或者浅色，而卷烟的燃烧碳线为黑色或者深色，本发明根据这一特征，可实时跟踪卷烟燃烧位置。根据燃烧碳线的位置，跟踪卷烟燃烧位置。
如图5和图6，两张图片中，在卷烟抽吸非弹灰抽吸过程中，出现了明显的裂口面积变化，表明出现了飞灰或落灰情况，进行统计处理。图5中方框标识的位置，出现了较大裂口面积变化率，即为出现飞灰的位置。
应用实例
本实例在检测过程中，采集图像过程中采用LED光源对样品检测环境进行打光和补光，目的是确保检测环境光线充分、稳定，减少外界环境对图像采集的干扰。
检测样品：本测定方法适用于全部烟支规格样品，在本实例中以常规烟支24.3mm圆周，84.0mm长度为测定样品说明，按照上述实施方式进行检测，共检测3种不同卷烟规格。
测试配置：控制系统：分析软件：FZ-PanDA(OMRON日本)；打光光源：JL-LR-100X30(嘉励国产)；摄像头型号：FH-SC04(日本OMRON)，镜头型号：3Z4S-LE(日本OMRON)。
测试环境：温度：(22±2)℃，相对湿度：(60±5)％。
操作步骤如发明内容所述，具体按照以下步骤进行：
步骤(1)，将待测卷烟样品单层均匀地置于GB/T 16447规定的环境中平衡48h；
步骤(2)，将平衡处理好的样品卷烟夹持在卷烟夹持器上，并调整图像采集装置的位置，使得整只卷烟位于各摄像头图像采集中心位置；
步骤(3)，打开图像采集装置、图像处理装置；
步骤(4)，点燃检测样品卷烟，启动机械手仿真抽吸及卷烟抽吸气缸，在ISO标准抽吸条件下进行检测。机械手仿真抽吸动作设置按照伏案等待时间40s、伏案持烟角度30°，抽吸后手腕翻转90°进行设置；当裂口面积变化超过1mm 2则判断为出现了新的缺损；
步骤(5)，图像采集装置按照设定每隔1s采集一张图像，实时采集卷烟燃烧过程图像；
步骤(6)，图像处理装置对采集到的图像进行条件筛选后，对比在非弹灰过程中，前后采集到的图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，根据差异计算出飞灰量，用面积表征。
步骤(7)，对检测中出现飞灰的样品进行时间和图像记录，每个规格样品选取两个样品进行飞灰结果表征，具体如表1和图7所示。
表1各规格样品不同拍摄角度飞灰情况
Figure PCTCN2021073110-appb-000001
Figure PCTCN2021073110-appb-000002
由实例可见，不同规格卷烟在燃烧过程中均存在一定程度的飞灰。采用本发明方法能有效采集和量化卷烟飞灰，用于对比卷烟产品飞灰质量差异，指导卷烟产品优化升级。
以上显示和描述了本发明的基本原理、主要特征和本发明的优点。本行业的技术人员应该了解，本发明不受上述实施例的限制，上述实施例和说明书中描述的只是说明本发明的原理，在不脱离本发明精神和范围的前提下，本发明还会有各种变化和改进，这些变化和改进都落入要求保护的本发明范围内。本发明要求保护范围由所附的权利要求书及其等效物界定。

Claims (10)

  1. 一种基于机器视觉的卷烟飞灰检测装置，其特征在于，包括仿真人体抽吸动作机械手(1)、卷烟夹持器(2)、烟支抽吸管(3)、弹灰机构(4)、图像采集装置(5)和图像处理装置(6)；
    仿真人体抽吸动作机械手(1)工作端处固定连接有卷烟夹持器(2)；
    卷烟夹持器(2)与烟支抽吸管(3)相连；
    弹灰机构(4)设于仿真人体抽吸动作机械手(1)外围；
    图像处理装置(6)与图像采集装置(5)相连；
    图像采集装置(5)也安装在仿真人体抽吸动作机械手(1)工作端；
    所述的仿真人体抽吸动作机械手(1)用于模拟人体抽烟动作；
    所述的卷烟夹持器(2)用于夹持不同圆周等规格差异的卷烟；
    所述的烟支抽吸管(3)连接抽吸气缸，用于抽吸卷烟；
    所述的弹灰机构(4)用于仿真抽吸过程中点弹卷烟烟灰；
    所述的图像采集装置(5)用于同步采集卷烟在抽吸过程中卷烟燃烧灰柱图像；
    所述的图像处理装置(6)用于对所述的图像采集装置(5)在仿真抽吸过程中同步采集到的卷烟燃烧灰柱图像进行对比分析，对比不进行弹灰条件下的图像，通过图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
    其中，对比的两张图像之间不存在弹灰动作。
  2. 根据权利要求1所述的基于机器视觉的卷烟飞灰检测装置，其特征在于，图像采集装置(5)包括N个摄像头，N≥2。
  3. 根据权利要求1所述的基于机器视觉的卷烟飞灰检测装置，其特征在于，弹灰机构(4)包括位于机械臂外围的弹烟支架(7)，安装于弹烟支架(7)上的驱动电机(8)，设置于驱动电机(8)输出端的拔杆(9)。
  4. 根据权利要求1所述的基于机器视觉的卷烟飞灰检测装置，其特征在于，仿真人体卷烟抽吸动作时，采用ISO、FTC、Massachusetts或加拿大深度抽吸模式。
  5. 根据权利要求1所述的基于机器视觉的卷烟飞灰检测装置，其特征在于，图像处理装置(6)在判断出现飞灰后，在设定检测样品燃烧长度范围内，对整支烟的出现飞灰量进行统计。
  6. 一种基于机器视觉的卷烟飞灰检测方法，采用权利要求1～5任意一项所述的基于机器视觉的卷烟飞灰检测装置进行测定，其特征在于，包括如下步骤：
    步骤(1)，将卷烟夹持在卷烟夹持器上，并进行调整，使得整只卷烟在图像采集装置的摄像头采集的画面中；
    步骤(2)，点燃卷烟夹持器上的卷烟，通过图像采集装置实时采集卷烟在仿真抽吸过程中的图像；
    步骤(3)，图像处理装置对采集到的图像进行条件筛选后，对比在非弹灰过程中，前后采集到的图像中卷烟燃烧灰柱裂口面积的变化，来判断卷烟燃烧灰柱是否出现了新的缺损，如出现新的缺损，则判断出现飞灰，用新出现的裂口面积来表征飞灰量；
    之后根据选择检测样品的燃烧长度范围，对该烟支出现飞灰的区域的数量及各区域的面积进行统计。
  7. 根据权利要求6所述的基于机器视觉的卷烟飞灰检测方法，其特征在于，图像采集装置实时采集卷烟燃烧过程的图像时，每隔1s采集一张图像。
  8. 根据权利要求6所述的基于机器视觉的卷烟飞灰检测方法，其特征在于，判断卷烟燃烧灰柱是否出现了新的缺损的具体方法是：每隔1s，对比前后采用的两张图片是否出现了明显的灰度变化，若出现了明显的裂口面积变化，则表明出现了新的缺损。
  9. 根据权利要求6所述的基于机器视觉的卷烟飞灰检测方法，其特征在于，明显的裂口面积变化取值范围1-20mm 2。
  10. 根据权利要求6所述的基于机器视觉的卷烟飞灰检测方法，其特征在于，计算灰柱裂口面积步骤如下：
    第一步，根据炭线位置和灰柱末端位置获得灰柱的大致区域；
    第二步，对灰柱大致区域图片进行第一次二值化，再查找轮廓，获得准确的灰柱区域；
    第三步，对准确的灰柱区域进行第二次二值化，获得灰柱的裂口区域，从而计算出当前图片灰柱的裂口面积。
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